📈 Major Stock Analysis & Technical Indicator Visualization

This project is a comprehensive stock data analysis tool built using Python and Jupyter Notebook. It enables you to fetch historical market data, compute key technical indicators, and visualize trends, aiding in better trading or investment decisions.

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📁 Project Structure

• Stock_Analysis.ipynb – Main notebook for data loading, visualization, and technical indicator computation.
• data/ – (Optional) Folder to store any downloaded CSV files or backups.
• charts/ – (Optional) Output directory for saved plots.

📌 Features

• 🗓️ Fetch stock data using Yahoo Finance (yfinance)
• 📊 Compute technical indicators like:
  • Simple Moving Average (SMA)
  • Exponential Moving Average (EMA)
  • Relative Strength Index (RSI)
  • Moving Average Convergence Divergence (MACD)
• 🖼️ Plot price charts with indicators and signals
• 🧠 Perform trend and momentum analysis
• 🧾 Simple signal generation (Buy/Sell zones)

🚀 How to Run

1. Install Dependencies

   Run the following command to install all required Python packages:

   pip install pandas numpy matplotlib seaborn yfinance ta
   

📌 Features

• ✅ Stock Data Download via yfinance
• ✅ Interactive Charting with price overlays
• ✅ Built-in Indicators:
  • Moving Averages (SMA, EMA)
  • MACD & Signal Line
  • Relative Strength Index (RSI)
• ✅ Buy/Sell Signal Zones (based on RSI thresholds or MA crossovers)
• ✅ Modular Codebase for easy customization
• ✅ No API key required (free public data)

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🧰 Tech Stack

🖥️ Programming Language

• Python 3.7+

📦 Libraries & Tools

Library	Purpose
pandas	Data wrangling and time series
numpy	Numerical computations
matplotlib	Basic visualization
seaborn	Statistical & styled visualizations
yfinance	Fetching historical stock data
ta	Pre-built technical indicators
jupyter	Notebook for interactive workflows

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